Logical storage systems (e.g., including logical components backed by physical storage devices) often employ one or more types of data replication in order to protect against data loss in the event of a system failure (e.g., hardware crash, file corruption, or the like). For example, the logical components of a logical storage system may be organized in various types of redundant array of independent disks (RAID) configurations. When a logical component goes offline (e.g., fails) and then reconnects, it may be resynchronized using other logical components in the system.
In distributed logical storage systems, such as those shared by a plurality of users, it may be useful to estimate a workload (e.g., amount of resources) required to resynchronize a logical component. For example, such estimates may allow for appropriate allocation of bandwidth for resynchronization tasks or may allow a user to determine a best time to initiate a resynchronization task. In basic cases, this estimate may be roughly based on the total allocated size of the logical component to be resynchronized. This technique may not result in an accurate estimate in many cases, however, such as in systems involving thin-provisioned data. Thin-provisioning involves allocating disk storage space in a flexible manner among multiple users, based on the minimum space required by each user at any given time, rather than allocating all storage space in advance. Because an allocated size of a logical component may be quite different from a physically used size of the logical component on a physical storage device in such systems, estimating a workload required to resynchronize a logical component may be difficult. Furthermore, when a logical storage system involves a complex configuration including different types of redundancy, it may be particularly challenging to estimate a workload required to resynchronize a logical component. As such, there is a need for improved methods for estimating a workload required to resynchronize a logical component in a logical storage system.